Accuracy measures for machine learning: Archives

Accuracy Measures for Machine Learning

This article is a brief introduction to some of the ideas behind measuring the accuracy of supervised machine learning tools.

By Dr Tom Whitehead

Introduction

This article is a brief introduction to some of the ideas behind measuring the accuracy of supervised machine learning tools. The first half deals with classification algorithms; those that decide which of several classes a sample belongs to. The chief measure of accuracy there is the confusion matrix, from which a whole host of other statistics may be extracted. The second half of this article deals with regression algorithms, which give a predicted numerical value for some outputs from known inputs.